教學大綱與進度

課程基本資料：

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
115-1	366648	大數據分析	1	3.0	3	★	王正豪 鄭麗珍	管理外國學生專班 資財所	19	0	資財所和IMBA合開

教學大綱與進度：

教師姓名	鄭麗珍　教師諮商時間(Office Hours)
Email	jessicacheng@mail.ntut.edu.tw
最後更新時間	2026-06-04 13:52:58
課程大綱	本課程介紹大數據在各個領域決策制定的應用，課程內容包括大數據分析與應用、大數據管理、大數據分法與策略、資料探勘介紹、資料探勘方法、大數據平台、大數據行銷實務、大數據個案分析、期末專題製作與報告。學生可以經由多個案例學習大數據的應用實務、目前技術與未來發展方向。這門課要閱讀期刊論文 且要熟悉 python This course explores the rapidly developing fields of big data for the efficiency of decision making in various fields. The topics are about basic concepts of data manipulations, analytic, and communications which are including: introduction to big data; basic knowledge of data mining; special topics of big data in business Analytics, and data analytic project. The course will help students careful consideration of what is desired from big data, how big data analytic to add value to business, etc. Students can gain a strong data science knowledge set and techniques via in-depth case studies, most current readings and experiences, and most current and future technology exploration.
課程進度 (1-16週)	Topic I: data preprocessing and DM tool 1. Be familiar of business analytics potential and dangers in today’s data rich-environment 2. Gain experience using key data mining methods of classification, prediction, data reduction and exploration 3. Know how to decide when to use which technique 4. Be able to implement major data mining techniques using software Topic II paper study project development
彈性學習 (17-18週)	類別 　 內容 　 時數 (小時) 　 學習成果 　 評量比例
評量方式與標準	paper study and presentation and feedback：20％ Hand on lab 40% Final team project report and presentation: 40% This course also discusses the journal paper to enhance the students' theoretical base NOTE: This is an advanced course. Student also should familiar with python
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：是 Data Mining for Business Analytics [Python Edition](link is external), John Wiley & Sons, 2019
課程諮詢管道	lijen.cheng@gmail.com name class and question
延伸教學與資源	● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
課程對應SDGs指標	SDG3：良好健康和福祉（Good Health and Well-being） SDG4：優質教育（Quality Education）
課程是否導入AI	● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools） ● 使用生成式AI進行課堂即時互動（Use generative AI for real-time classroom interaction） ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）
備註	teams